Despite hundreds of linkage and association studies, including eight recent case-control genome-wide association studies (GWAS), there has been limited progress in identifying specific genes associated with depression. Epidemiological evidence indicates that life stress is a key factor in the etiology of depression. Indeed, there is growing recognition that accounting for stress facilitates the identification of genes important in the development of depression. Because of methodological limitations however, gene x stress studies have been limited from utilizing the broad-scale genomic approaches that have been successful in identifying genes in other complex disorders. Our long-term goal is to elucidate the pathophysiological architecture underlying depression to facilitate the development of improved treatments. Our objective in this application is to identify genetic variants associated with the development of depression under stress by utilizing medical internship as a model. The power and effectiveness of traditional gene x stress interaction studies have been compromised by the following study design limitations: 1) substantial variation in the type and intensity of stress between subjects 2) retrospective design and 3) loss of power due to tests of statistical interaction. Designing methods to overcome these limitations has been difficult because the onset of chronic stress is difficult to predict beforehand and the type of stress encountered by individuals varies greatly. Medical internship, the first year of professional physician training, presents a unique situation in which we can prospectively predict the onset of a uniform, chronic stressor and a dramatic increase in depressive symptoms. We hypothesize that both common and rare SNPs from across the genome will interact with internship stress to impact depressive symptom phenotypes. To test this hypothesis, we propose the following three specific aims: 1) identify longitudinal patterns of depressive symptoms under internship stress and factors associated with the depressive symptom patterns, 2) identify common and rare, functional genetic variants associated with depressive symptoms and depressive symptom trajectories during internship stress using cutting edge GWAS and Exome chip analysis and 3) assess whether significant associations with depressive symptoms in the intern sample replicate in other depression samples. Our approach is innovative because it takes advantage of a naturally occurring stress to overcome limitations of existing studies and allows us to perform a broad-scale, longitudinal cohort gene x stress study. This project is significant because it has the potential to identify key genetic factors involved in depression under stress, an advance that holds promises in predicting treatment response and identifying novel targets for antidepressant development.
Major depression affects approximately 1 in 6 Americans and it will soon be second to heart disease in terms of disease-associated disability according to the World Health Organization. Unfortunately, currently available depression treatments are only partially effective. This project is designed to uncover new biological pathways that can be targeted to develop more effective and more precise anti-depressant treatments.
|Ridout, Kathryn K; Ridout, Samuel J; Price, Lawrence H et al. (2016) Depression and telomere length: A meta-analysis. J Affect Disord 191:237-47|
|Rotenstein, Lisa S; Ramos, Marco A; Torre, Matthew et al. (2016) Prevalence of Depression, Depressive Symptoms, and Suicidal Ideation Among Medical Students: A Systematic Review and Meta-Analysis. JAMA 316:2214-2236|
|Mata, Douglas A; Ramos, Marco A; Kim, Michelle M et al. (2016) In Their Own Words: An Analysis of the Experiences of Medical Interns Participating in a Prospective Cohort Study of Depression. Acad Med 91:1244-50|
|Fried, E I; Nesse, R M; Guille, C et al. (2015) The differential influence of life stress on individual symptoms of depression. Acta Psychiatr Scand 131:465-71|
|Fiedorowicz, Jess G; Ellingrod, Vicki L; Kaplan, Mariana J et al. (2015) The development of depressive symptoms during medical internship stress predicts worsening vascular function. J Psychosom Res 79:243-5|
|Byrd, Amy L; Wright, Aidan G C; Sen, Srijan et al. (2015) Reply to: the liptak-stouffer test for meta-analyses. Biol Psychiatry 77:e3-4|
|Guille, Constance; Zhao, Zhuo; Krystal, John et al. (2015) Web-Based Cognitive Behavioral Therapy Intervention for the Prevention of Suicidal Ideation in Medical Interns: A Randomized Clinical Trial. JAMA Psychiatry 72:1192-8|
|Mata, Douglas A; Ramos, Marco A; Bansal, Narinder et al. (2015) Prevalence of Depression and Depressive Symptoms Among Resident Physicians: A Systematic Review and Meta-analysis. JAMA 314:2373-83|
|Gruppen, Larry D; Stansfield, R Brent; Zhao, Zhuo et al. (2015) Institution and Specialty Contribute to Resident Satisfaction With Their Learning Environment and Workload. Acad Med 90:S77-82|
|Fried, E I; Nesse, R M; Zivin, K et al. (2014) Depression is more than the sum score of its parts: individual DSM symptoms have different risk factors. Psychol Med 44:2067-76|
Showing the most recent 10 out of 15 publications